Williams, Leon - Associate SupervisorAccording to the World Health Organisation, billions of people lack access to
basic sanitation facilities and services, resulting in estimated 2.9 million cases of
diseases and 95,000 deaths each year. This is because poor planning, design,
maintenance, and access in traditional sanitation networks. Nowadays,
intelligent sanitation systems leveraging the Internet of Things (IoT) technology
can provide efficient and sustainable services, incorporating sensors, hardware,
software, and wireless communication. Furthermore, advanced data analytics
tools combined with the intelligent sanitation systems can provide a deeper
insight into operations, make informed decisions, and enhance user experience,
thereby improving sanitation services.
The thesis provides a comprehensive review of literature on intelligent
sanitation systems from both academic and industrial perspectives, with the
objective of identifying recent advances, research gaps, opportunities, and
challenges. Existing solutions for intelligent sanitation are fragmented and
immature due to a lack of a unified framework and tool. To address these
issues, the thesis introduces a generalised Sanitation-IoT (San-IoT) framework
to manage sanitation facilities and a standardised Sanitation-IoT-Data Analytics
(San-IoT-DA) tool to analyse sanitation data. The framework and tool can serve
as a foundation for future research and development in intelligent sanitation
systems. The San-IoT framework can enhance the connectivity, operability, and
management of IoT-based sanitation networks. The San-IoT-DA tool is
designed to standardise the collection, analysis, and management of sanitation
data for providing efficient data processing and improving decision making. The
feasibility of the proposed framework and tool was evaluated on a case study of
the Cranfield intelligent toilet. The San-IoT framework has the potential to
enable system monitoring and control, user health monitoring, user behaviour
analysis, improve water usage efficiency, reduce energy consumption, and
facilitate decision-making among global stakeholders. The San-IoT-DA tool can
detect patterns, identify trends, predict outcomes, and detect anomalies. The
thesis offers valuable insights to practitioners, academics, engineers,
policymakers, and other stakeholders on leveraging IoT and data analytics to
improve the efficiency, accessibility, and sustainability of the sanitation industry.PhD in Desig
